Inpaints missing imaging data from boundary data

Smooths data along the boundary into the missing region.

basicInPaint(img, paintMask, speedimage = NULL, its = 0, gparam = 0.05)

Arguments

img	antsImage to be approximated / painted
paintMask	painting mask with values 1 or values 1 and 2 - if there is a 2 then it will learn from label 1 to paint label 2. should cover the brain.
speedimage	- larger means faster/better
its	- iterations of graddescent
gparam	- graddescent param e.g. 0.05

Value

inpainted image

Examples

set.seed(123)
fi<-abs(replicate(100, rnorm(100)))
fi[1:10,]<-fi[,1:10]<-fi[91:100,]<-fi[,91:100]<-0
mask<-fi
mask[ mask > 0 ]<-1
mask2<-mask
mask2[11:20,11:20]<-2
mask<-as.antsImage( mask2  )
fi<-as.antsImage( fi )
fi<-smoothImage( fi, 3 )
painted<-basicInPaint( fi, mask )
if (FALSE) {
# lmask<-antsImageRead( "brainmask.nii.gz", 2 )
# limg<-antsImageRead( "r16slice_lesion.nii.gz", 2 )
# mm<-basicInPaint(limg,lmask)
# plot(mm)
# mm2<-basicInPaint(limg,lmask,its=10,gparam=0.05)
# plot(mm2)
}